All about the high inside fastball

What exactly is a high inside fastball?

“Well, duh, Nick. A high inside fastball is a pitch that is high and… wait for it… inside, hence the name. You don’t seem to be very sharp, I think I’m going to stop reading now.”

While the question may seem stupid, it’s necessary to define the pitch so we can take a look at it in more detail. For one, I’m interested in looking at pitches in the high inside corner of the strike zone, not ones that are actually high and inside. The reason for this? I don’t know, it seemed more interesting to me. Anyway, using the called strike zone coordinates for left-handed and right-handed hitters that John Walsh found here, I divided the zone into nine equal parts.

For a RHH, a high inside fastball is between -.333 and -1 feet from the center of the plate, and between 2.93 and 3.5 feet above the ground; and for a LHH, it’s between .125 and .825 feet from the center of the plate, and between 2.86 and 3.4 feet above the ground. I included all four-seam, two-seam and “normal” fastballs, mainly to get a bigger sample size, but I excluded sinkers and cutters.

Okay, so why should we care about them?

Well, for one, they are really freaking good. Using the methodology detailed by Walsh, I calculated the run value per 100 pitches for all high inside fastballs from 2007-2009:

Number

rv100

RHP to RHH

16518

-3.03

RHP to LHH

13166

-2.73

LHP to RHH

8514

-2.21

LHP to LHP

4145

-2.75

These are from the pitcher’s perspective, so the lower the number the better. For reference, the best fastball in baseball this year among qualifiers belongs to Chris Carpenter at 2.01 runs better than average. So simply throwing a fastball on the high inside corner turns an average fastball into the best in baseball!

Actually, it’s not quite that simple. Pitchers who have the guts and the command to challenge batters up and in are generally very good pitchers, so the run values of the high inside fastball may be inflated due to selection bias. So I subtracted the rv100 of each pitcher’s fastball that was thrown up and in by the overall run value of the fastball. I got a weighted rv100 of -2.34, so it appears that there is no bias.

How much does speed matter?

Pitch speed is obviously one of the most important facets of pitching. In most situations, you would always prefer the guy with the 98 mph fastball to the guy with the 88 mph one. However, when going up and in, does it make that much of a difference? If Joel Zumaya goes up and in with his triple-digit heater, is it going to be better than J.P. Howell’s 87 mph junk? To answer that I looked at the rv100 for six different speed groupings, and split it up by batter and pitcher hand:

Speed

RHP to RHH

RHP to LHH

LHP to RHH

LHP to LHH

Average

<87

0.84

-1.94

-0.75

-1.91

-0.83

87-89

-3.92

-2.40

-1.73

-1.09

-2.47

89-91

-2.72

-2.96

-2.51

-2.74

-2.74

91-93

-2.71

-2.62

-1.84

-3.56

-2.59

93-95

-3.94

-3.53

-4.60

-2.76

-3.81

95-97

-3.21

-2.70

-2.61

-5.68

-3.06

>97

-3.76

-2.52

*

*

-3.13

*Too small of a sample size

It’s a little hard to make sense of those data. When you take the averages, the effectiveness of a high inside fastball rises from a little bit better than average when it’s thrown below 87 mph and peaks from 93-95 mph, and then drops but plateaus at an above-average rate for the next speed groupings. However, when you compare each subgroup (batter and pitcher handedness) to themselves, it isn’t so clear.

For example, from a RHP to a RHH, an 88 mph fastball up and in is just as effective as a 94 mph fastball, and more effective than pitches thrown harder than that. That comes in a very big sample size as well, more than 1,700 pitches for each group, so you can’t just chalk it up to random variation. That effect is also present on fastballs to a LHH from a RHP. Although the the rv100 dips from 93-95 mph, the rest of the groupings are virtually indistinguishable from each other.

Another interesting nugget is that the high inside fastball from a LHP to a LHH that’s at least 95 mph is nearly six runs better than average per 100 pitches. The main reason for that is there have been only 121 such pitches over the past three years. Three years! Even if there were something extra special about that pitch, you can’t tell from the actual data.

What about pitch sequencing?

So we’ve found that pitch speed has a detectable, but sporadic, impact on the effectiveness of the high inside fastball, but what about pitch sequencing? Is a high inside fastball better when thrown following a fastball or an off-speed pitch, and perhaps more interestingly, how does a high inside fastball impact the pitch that follows it?

Let’s check out the first question first. Sorting by batter and pitcher handedness, here is how much the high inside fastball is improved on based on the previous pitch thrown (in the same at bat obviously):

Previous pitch

RHP to RHH

RHP to LHH

LHP to RHH

LHP to LHH

Average

Fastball

-0.36

-0.23

-1.02

-0.59

-0.47

Changeup

0.39

0.28

1.79

2.05

0.82

Curveball

0.33

1.34

1.09

0.51

0.91

Slider

-0.17

1.33

0.70

0.63

0.44

I bet you were expecting the high inside fastball to be most effective when thrown after an off-speed pitch. So was I. It turns out to be quite the opposite. On average, a high inside fastball is always more effective when thrown after another fastball. In fact, a high inside fastball is actually significantly worse than average when thrown after an off-speed pitch.

That actually shouldn’t surprise you. A while back, Josh Kalk ran the numbers on how effective each pitch was based on the pitch that preceded it, and found that a fastball was always worse when it followed an off-speed pitch. That, along with what I found today, contradicts conventional wisdom that pitching backwards is an effective strategy.

Backing them off the plate

Another of the traditional claims of the high inside fastball is that it will improve the following pitches in the at-bat, because the batter is aware of that pitch and will be more timid. Now whether that is actually the case, I don’t know; however, we can see how much the run value of each pitch type improves when it’s thrown after a high inside fastballs:

Next pitch

RHP to RHH

RHP to LHH

LHP to RHH

LHP to LHH

Average

Fastball

0.38

0.11

-0.17

0.42

0.19

Changeup

0.11

0.57

-0.09

-1.88

0.16

Curveball

1.36

0.64

1.71

-0.68

0.94

Slider

0.01

0.50

-0.36

0.23

0.13

These results are really surprising. It turns out that all major pitch types are significantly worse than the high inside fastball. This isn’t a miscalculation either, at least I don’t think. From 2007-2009, when a curveball follows a fastball from a RHP pitcher to a RHH, the run value of that curveball is -.31 runs per 100 pitches. That’s consistent with the findings Kalk had in the link I posted above. However, once you add a qualifier for the “first” pitch, plugging in the restraints for the high inside fastball, the rv100 jumps way up to 1.01. It’s possible that it’s simply a function of sample size (there have been only 956 such pitches); but that’s still a huge swing.

So while the high inside fastball may actually back batters off the plate (I assume it does, but we can’t be sure), that actually has a negative affect on future pitches in the at-bat. Why that is the case needs to be studied in more detail; however, this article is becoming pretty long, so that will have to wait for another day.

Conclusion

We’ve see that regardless of batter or pitcher hand, and, for the most part, independent of pitch speed, the high fastball is an amazingly effective pitch. It also works much better off fastballs then it does off off-speed pitches, and actually makes the following pitches in the at-bat worse than they will normally be. Still, it remains one of the best pitches in baseball simply because of the value it has in itself.

So why don’t pitchers throw it all of the time? Well, there are two reasons. The first one has to do with Game Theory. The high inside fastball is so effective in part because it isn’t thrown that often. If every pitch were a fastball up and in, the batters would adjust and start to hit it much better.

The second reason is probably the more prominent one. Pitchers don’t have perfect control. In fact, a lot of them have pretty bad control. Even Roy Halladay has thrown a ball 96 times in his career with a 3-0 count, and he’s one of the good ones. So when a pitcher goes up and in with the fastball, the ball won’t always go where it’s intended.

And what happens when you try to go up and in and miss? Well, the most likely outcomes are that the ball ends up either high, inside, middle in or center up. As you can imagine, the value of fastballs in those locations is not as good as the ones up and in. The actual effect is best observed like this:

These may be a little hard to digest at first, but I promise you they are information. The first graph shows how good a fastball is in the high zone (as in the zone that I’ve been calling the high inside fastball zone), based on its horizontal location. It’s not labeled, but the y axis is rv100. I’ve also marked where the high inside fastball is. You can see that for both RHH and LHH, the value peaks inside the high inside zone. The second graph is the same thing, but for fastballs in the inside zone, based on their vertical location. Again, you see the value of a fastball peaks when it is high and inside.

You also should notice how much the value drops once you leave the shaded zones. That raises the concept of pitch leverage: The high inside fastball may be one of the best pitches to throw, but it is also one of the riskiest.

References & ResourcesPITCHf/x data from MLBAM and Sportvision, and I am eternally grateful that this stuff is still available to the public. The pitch classifications used were the ones provided by Gameday and unfortunately may not be 100 percent accurate. However, fastballs are pretty easy to classify, so I trust that they are pretty good.

Comments

Can we please see an analysis like this in regards to the count? Sequencing’s a start, but batters and pitchers are geared to expect certain pitches/speeds/locations on certain counts.

It appears that some pitchers are more skilled than others at throwing a given pitch for the desired effect on a given count (yes, that is a reference to John Lannan – I believe his ability to outperform his FIP comes from being able to throw any pitch on any count with a greater-than-average consistency) than others, but I’d like to *know* that.

I claim no scientific stats to back me up, but I do think the high hard one works. Every time I see a list of pitchers who are, or were, known to come in high and tight on a regular basis, it’s a list of winning pitchers.

Unless a pitcher can work both sides of the plate he’s not going to have much success.

My best guess? On 0-2 and 1-2, hitters are looking to just make contact whereas on favorable counts, they tend to grip-it-and-rip-it, knowing they have wiggle room. Also, I rarely see pitchers go that route—it’s usually high-hard-and-middle or soft-low-and-away. Perhaps there’s a selection bias there, too (i.e. the least effective pitchers try that and fail).

The difference between LHHs and RHHs on 3-2 *seems* to verify the stereotype that RHHs tend to be better high-ball hitters vs. LHHs, but I also wonder if the opposite selection bias is in there too (i.e. the most effective pitchers are able to do this and succeed).

Thanks for crunching the extra data!

Out of curiosity, do walks that result on taken 3-ball counts show up in that data? I would tend to think not, but I would further wonder if the

Great work – for starters. Any work done on the effect of pitch sequencing has to control for the pitcher and the count and even the batter if possible. But at the very least, the count and pitcher.

Basically, it has to be done like the “delta method” for aging and other similar-type studies. For example, with pitcher A on the mound, on a 1-2 count (preferably with the last pitch being the same result, ball or strike), what is the difference between the run value of a fastball after a fastball and a fastball after an off-speed pitch. Then you add up all those “deltas”. That is really the only the way to do it. If you just aggregate data for all pitchers, you run into huge selective sampling issues and you basically get results that have little meaning.

And like I said, unless you control for the batter, you might run into trouble as well. For example, let’s say that weak batters see a lot more fastballs (fb) in general and strong batters see more off-speed pitches (os). Your os-fb sequence might be populated by better hitters than your fb-fb sequence, for obvious reasons.

And I would not be surprised if conventional wisdom about throwing down and away (or just an off-speed pitch) after a high hard one is not correct or that changing pitches is not an effective strategy. Anything that is predictable can be and probably is exploited by batters. I have always thought that going with an off-speed pitch an inordinate percentage of the time (more than would be random) is a ridiculous strategy, even if you are changing the batter’s “eye level” or whatever you want to call it. I mean if Tim McCarver (or basically everyone in the ballpark or watching on TV) thinks that after a high hard one, the pitcher is going to throw a breaking pitch like 80% of the time, don’t you think that the batter would know that too and would be looking for it? Depending upon the count and the pitcher of course, the next pitch has to be as likely to be high and hard again as it is low and away or offspeed. When I say “as likely” I don’t mean 50/50 or all pitches with equal likelihood. I simply mean whatever the count, the pitcher’s repertoire, the batter’s strengths and weaknesses, and the game situation would dictate.

BTW, does rv100 include the value of a ball or a strike as well as the value of a ball in play? IOW, if a pitch is not put into play, the rv100 value is the average value of the after count minus the before count (times 100)?

I think what MGL is getting at with his last sentence is this: You’ve restricted your sample of pitches to only include those thrown for strikes. Presumably that alone will lower (improve) the run value of those pitches.

For example, you report Chris Carpenter as having the best fastball in the game this year, at 2.01. If you restrict it to fastballs thrown in the strike zone, I’m guessing it will be higher than that, though I have no idea by how much. For the sake of comparing to other numbers, it would be nice to have a better baseline of the value of fastballs *in the strike zone* as opposed to all fastballs.

Thanks MGL and dks. I had already planned to do a full article soon looking solely at pitch sequencing, so I’ll employ all of your suggestions.

However, I believe rv100, or at least the one I’m using, already takes into account the count. You take the linear weights of each event – the expected linear weights of that count to get the net run value. I assume that’s a powerful enough adjustment to make up for the difference’s in count.

As for adjusting for pitch and hitter, that makes sense. I’m not sure why I didn’t do that in the original article (probably just being lazy, as it takes a bit more work).

As for giving the weights of pitches in the strike zone, I’m just not sure that’s relevant, at least for the purposes of pitch sequencing. I’m already adjusting for count, so that doesn’t really matter in terms of strikes and balls. I’m probably wrong though. As for aesthetic purposes, that works, but I’m not sure I want to doctor the numbers too much.

Also, when looking at preceding pitches, it would be interesting to see if preceding off-speed pitches were balls or strikes. Before looking at numbers, I would say that if pitcher can’t throw his off-speed stuff for strikes, hitters can sit on his fastball, and fastball would be less effective. But if pitcher can control all of his pitches, batter can’t just expect fastball after off-speed pitch, and fastball shouldn’t lose its effectiveness. Can you check that?

Like I said, I plan to devote an entire article to pitch sequencing, so I’ll separate by whether the previous pitch was a strike or not, and probably more interesting, what kind of strike was it (slider down in away, curveball in the dirt, fastball down the middle).